[issue4593] Documentation for multiprocessing - Pool.apply()

Jesse Noller added the comment: fixed in trunk, r68862, merged to 3k in r68863 -- resolution: -> fixed status: open -> closed ___ Python tracker ___

[issue4593] Documentation for multiprocessing - Pool.apply()

David M. Beazley <[EMAIL PROTECTED]> added the comment: Actually, you shouldn't discount the potential usefulness of running apply() in all of the worker nodes. A lot of people coming from parallel programming know about things like global broadcasts, reductions, and so forth. For example, i

[issue4593] Documentation for multiprocessing - Pool.apply()

Jesse Noller <[EMAIL PROTECTED]> added the comment: Ah, I see what you're talking about David. Good catch. It wouldn't make sense to run the apply() in all of the workers, as apply() is a single function(...) call. map() however is done in parallel amongst all workers.

[issue4593] Documentation for multiprocessing - Pool.apply()

Changes by Christian Heimes <[EMAIL PROTECTED]>: -- assignee: georg.brandl -> jnoller keywords: +easy nosy: +jnoller priority: -> normal stage: -> needs patch ___ Python tracker <[EMAIL PROTECTED]>

[issue4593] Documentation for multiprocessing - Pool.apply()

New submission from David M. Beazley <[EMAIL PROTECTED]>: The documentation for the apply() and apply_async() methods of a Pool object might emphasize that these operations execute func(*args,**kwargs) in only one of the pool workers and that func() is not being executed in parallel on all wor